Near real-time S-AIS: Recent developments and implementation possibilities for global maritime stakeholders

Abstract

The Automatic identification System (AIS) has been mainly designed to improve safety and efficiency of navigation, environmental protection, coastal traffic monitoring simplifying identification and communication. Additionally, historical AIS data have been used in many other areas of maritime safety, economic and environmental research. The probability of the detection of terrestrial AIS signals from space was presented in 2003, following the advancements in micro satellite technology. Through constant development, research and cooperation between governmental and private sectors, Satellite AIS (S-AIS) has been continuously evolving. Advancements in signal and data processing techniques have resulted in an improved detection over vast areas outside of terrestrial range. Some of the challenges of S-AIS technology include satellite revisit times, message collision and ship detection probability. Data processing latency and lacking the continuous real-time coverage made it less reliable for end user in certain aspects of monitoring and data analysis. Recent developments and improvements by leading S-AIS service providers have reduced latency issues. Complementing with terrestrial AIS and other technologies, near real-time S-AIS can further enhance all areas of the global maritime monitoring domain with emerging possibilities for maritime industry. A brief historical overview of the S-AIS system with recent developments of near real-time S-AIS technology and its current applications has been presented in this paper. Potential usage in cargo monitoring, terminal and port operations has been analyzed as well. Management of near real-time and historical S-AIS data can further improve analysis, planning organization and performance for global maritime supply chain stakeholders especially in liner schedule reliability. Algorithm for a dynamic near real-time organizational planning has also been analyzed in this paper. The proposed algorithm defines interdependence of the maritime shore stakeholders in the transport process as well as the actions undertaken in the following vessel arrival data.